Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Jouni Helske
Title: KFAS: Exponential Family State Space Models in R
Abstract: State space modeling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes the R package KFAS for state space modeling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modeling is presented.

Page views:: 6350. Submitted: 2015-05-06. Published: 2017-06-09.
Paper: KFAS: Exponential Family State Space Models in R     Download PDF (Downloads: 2949)
Supplements:
KFAS_1.2.8.tar.gz: R source package Download (Downloads: 264; 609KB)
v78i10.R: R replication code Download (Downloads: 417; 11KB)
DOI: 10.18637/jss.v078.i10

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.